公开(公告)号：US20170364160A1

公开(公告)日：2017-12-21

申请号：US15624724

申请日：2017-06-16

Applicant: TEXAS INSTRUMENTS INCORPORATED

Inventor： Gregory Jan Malysa ,  Murtaza Ali ,  Dan Wang ,  Lorin Paul Netsch

IPC: G06F3/01 ,  G06F3/0487

CPC classification number: G06F3/017 ,  G01S7/415 ,  G01S13/34 ,  G01S13/584 ,  G01S2007/356 ,  G06F3/01 ,  G06F3/03 ,  G06F3/0487 ,  G06K9/00335 ,  G06K9/6297 ,  G06N7/005

Abstract: A gesture recognition system is shown using a 77 GHz FMCW radar system. The signature of a gesturing hand is measured to construct an energy distribution in velocity space over time. A gesturing hand is fundamentally a dynamical system with unobservable “state” (i.e. the type of the gesture) which determines the sequence of associated observable velocity-energy distributions, therefore a Hidden Markov Model is used to for gesture recognition. A method for reducing the length of the feature vectors by a factor of 12 is also shown, by re-parameterizing the feature vectors in terms of a sum of Gaussians without decreasing the recognition performance.

公开(公告)号：US11054913B2

公开(公告)日：2021-07-06

申请号：US16719616

申请日：2019-12-18

Applicant: TEXAS INSTRUMENTS INCORPORATED

Inventor： Gregory Jan Malysa ,  Murtaza Ali ,  Dan Wang ,  Lorin Paul Netsch

IPC: G06F3/0487 ,  G06F3/01 ,  G01S13/34 ,  G01S13/58 ,  G01S7/41 ,  G06F3/03 ,  G06K9/62 ,  G06K9/00 ,  G01S7/35 ,  G06N7/00

Abstract: A system includes a frequency modulated continuous wave (FMCW) transceiver, a processor, and a memory. The memory stores program instructions that, when executed by the processor, cause the system to receive a signal representative of an FMCW signal reflected from an object of interest, apply a first Fourier transform to the signal to obtain range data, identify a subset of the range data corresponding to a region of interest, apply a second Fourier transform on the identified subset of the range data to obtain velocity data corresponding to the identified subset of the range data, and identify a gesture performed by the object of interest based on at least a portion of velocity data.

公开(公告)号：US10514770B2

公开(公告)日：2019-12-24

申请号：US15624724

申请日：2017-06-16

Applicant: TEXAS INSTRUMENTS INCORPORATED

Inventor： Gregory Jan Malysa ,  Murtaza Ali ,  Dan Wang ,  Lorin Paul Netsch

IPC: G06F3/01 ,  G06F3/0487 ,  G01S7/41 ,  G01S13/34 ,  G01S13/58 ,  G06F3/03 ,  G06K9/00 ,  G06K9/62 ,  G01S7/35 ,  G06N7/00

Abstract: A gesture recognition system is shown using a 77 GHz FMCW radar system. The signature of a gesturing hand is measured to construct an energy distribution in velocity space over time. A gesturing hand is fundamentally a dynamical system with unobservable “state” (i.e. the type of the gesture) which determines the sequence of associated observable velocity-energy distributions, therefore a Hidden Markov Model is used to for gesture recognition. A method for reducing the length of the feature vectors by a factor of 12 is also shown, by re-parameterizing the feature vectors in terms of a sum of Gaussians without decreasing the recognition performance.